Cardiovascular diseases (CVDs) or commonly known as heart diseases are the leading cause of deaths globally, amounting to nearly 17.9 million deaths each year. More than 32% of deaths worldwide are caused by heart diseases. It is a subject of grave importance for cardiologists (heart specialists) to diagnose and treat them as soon as possible.
Doctors analyze a variety of health parameters to understand and diagnose the heart condition of the patient. Such a process requires immense precision and excellent assessment for proper diagnosis. Their timing and description of the diagnosis could potentially mean the difference of life or death. Thus, there is a lot of stakes in their hands.
However, with the help of this AI classifier program, doctors could now cross reference their evaluation. With an outstanding accuracy of over 91%, it utilizes Random Forest Classifier algorithm as a powerful predictor of presence of a heart disease. Additionally, it could also be used to train other junior doctors for evaluating their diagnosis.
The dataset has been sourced from the UCI Repository, an established and reliable library for data sources. The data consists of several health details which are sensitive and must not be directly associated to any known particular patient. Therefore, for ethical purposes the identities of the patients have been kept as anonymous.